摘要
在Neyman-Pearson准则下,对于贝叶斯检测前跟踪算法,为了能够按照系统要求的虚警概率实时地设置检测阈值,该文在观测噪声为复高斯白噪声的情况下推导得到了检测阈值的近似闭式解。对于贝叶斯检测前跟踪算法,该文从似然比检测形式入手,推导了检测统计量的表达式,得到了系统虚警概率同检测阈值之间的关系,并在观测噪声为复高斯白噪声的情况下给出了检测阈值的近似闭式解。计算机仿真实验表明,利用该检测阈值的近似闭式解,可以按照系统要求的虚警概率实时地计算检测阈值,从而使得实际系统的虚警概率满足要求。
In order to set the detection threshold in real time according to the demanded false alarm probability for Bayesian track-before-detect under Neyman-Pearson criterion, this paper derives the closed-form solution of the detection threshold in white complex Gaussian noise. For the Bayesian track-before-detect, this paper starts from the likelihood ratio testing form, derives the relationship between the false alarm probability and the detection threshold in detail, and obtains the closed-form solution of the detection threshold in white complex Gaussian noise The simulation results show that the detection threshold can be ascertained in real time for Bayesian track-before-detect according to the false alarm orobabilitv in demand usin~ the presented aDnroAx^h.
出处
《电子与信息学报》
EI
CSCD
北大核心
2013年第3期524-531,共8页
Journal of Electronics & Information Technology
基金
国家自然科学基金(60901067)
新世纪优秀人才支持计划(NCET-09-0630)
长江学者与创新团队发展计划(IRT0954)资助课题